CN109359591B - Method for automatically identifying large-diameter shield tunnel mid-partition wall based on point cloud data - Google Patents
Method for automatically identifying large-diameter shield tunnel mid-partition wall based on point cloud data Download PDFInfo
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Abstract
The invention provides a method for automatically identifying a large-diameter shield tunnel mid-partition wall based on point cloud data, which comprises the following steps of: s1: acquiring point cloud data of each section of each channel of a large-diameter shield tunnel through a three-dimensional laser scanning device; s2: calculating an included angle theta formed by each scanning point and the corresponding vertical direction of the section; s3: extracting a first point cloud set and a second point cloud set of different types from the point cloud data according to the included angle theta; the categories comprise a tunnel duct piece end point cloud set and a mid-partition wall end point cloud set; s4: identifying and determining a category of the first and second sets of point clouds. According to the method for automatically identifying the large-diameter shield tunnel mid-board based on the point cloud data, the large-diameter shield tunnel mid-board can be automatically identified according to the point cloud data, and the manual operation time can be reduced.
Description
Technical Field
The invention relates to the field of automatic point cloud identification, in particular to a method for automatically identifying a large-diameter shield tunnel mid-partition wall based on point cloud data.
Background
In recent years, the development and utilization speed of underground space and the construction speed of infrastructure are increasing continuously in China, the shield tunnel technology is rapidly developed, and particularly in the field of river-crossing traffic tunnels, large-diameter shield tunnels are on the way. For the safety problems of ventilation, escape and the like during tunnel operation, an intermediate wall is required to be arranged in the tunnel to enable the tunnel uplink and downlink to operate in two independent spaces.
The three-dimensional laser scanning technology is a novel measurement technology developed in recent years, and has the advantages of high measurement efficiency, rich measurement information, high measurement precision and the like. At present, three-dimensional laser scanning of a tunnel is mainly used for obtaining tunnel axes, full sections, horizontal diameters, inner wall laser reflectivity images and other measurement results, one side of the tunnel section is arc-shaped and the other side of the tunnel section is in a linear section shape due to the arrangement of the intermediate wall in a large-diameter shield tunnel, inconvenience is brought to automatic ellipse fitting and diameter obtaining, the arc end and the linear section end need to be judged manually, and the horizontal diameter is obtained through arc fitting and linear fitting respectively.
Therefore, in order to reduce the manual operation time and fully utilize the advantages of the three-dimensional laser scanning technology, a method for automatically identifying the middle wall of the large-diameter shield tunnel according to the point cloud data is not available and is needed.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides the method for automatically identifying the large-diameter shield tunnel mid-board based on the point cloud data, which can automatically identify the large-diameter shield tunnel mid-board according to the point cloud data and can reduce the manual operation time.
In order to achieve the aim, the invention provides a method for automatically identifying a large-diameter shield tunnel mid-partition based on point cloud data, which comprises the following steps:
s1: acquiring point cloud data of each section of each channel of a large-diameter shield tunnel by using a three-dimensional laser scanning device, wherein the point cloud data comprises three-dimensional coordinates (X, Y and Z) of each scanning point in each section, wherein X represents a coordinate value of an X axis of the current section, Y represents a coordinate value of a Y axis of the current section, and Z represents a coordinate value of a Z axis of the current section; the X axis is arranged along the horizontal direction of the section, the Y axis is arranged along the axial direction of the current section, and the Z axis is arranged along the vertical direction of the current section;
s2: calculating an included angle theta formed by each scanning point and the corresponding vertical direction of the section;
s3: extracting a first point cloud set and a second point cloud set of different types from the point cloud data according to the included angle theta; the categories comprise a tunnel duct piece end point cloud set and a mid-partition wall end point cloud set;
s4: identifying and determining a category of the first and second sets of point clouds.
Preferably, the included angle θ faces the positive direction of the X axis of the current cross section and is a positive value, and the included angle θ faces the negative direction of the X axis of the current cross section and is a negative value.
Preferably, the step of S3 further comprises the steps of:
s31: setting a first included angle range and a second included angle range;
s32: extracting the point cloud data of which the included angle theta is within the first included angle range from the point cloud data to form a first point cloud set; and extracting the point cloud data of which the included angle theta is within the second included angle range from the point cloud data to form the second point cloud set.
Preferably, the first included angle range is: -127 ° < θ < -34 °; the second included angle range is as follows: 34 DEG < theta < 127 deg.
Preferably, the S4 further comprises the steps of:
and performing straight line fitting on the first point cloud set and the second point cloud set by adopting a least square method, wherein a straight line equation is as follows: x-k-y + b, where k represents slope and b represents intercept;
respectively calculating the mean error after straight line fitting of the first point cloud set and the second point cloud set;
comparing the sizes of the two intermediate errors, wherein the first point cloud set or the second point cloud set corresponding to the smaller intermediate error is the intermediate wall endpoint cloud set; the first point cloud set or the second point cloud set corresponding to the larger medium error is the tunnel segment end point cloud set.
Preferably, the step of calculating the medium error comprises:
establishing an error equation vn：vn＝yn·k+b-xn(1)；
Wherein x isnIs the coordinate value of the current section X axis of the point cloud data of the nthnThe coordinate value of the current section Z axis of the nth point cloud data is obtained;
according to said error equation vnEstablishing an error matrix V;
wherein
Satisfy VTMin represents VTThe minimum value of V; solving to obtain:
calculating the medium error by using a medium error formula:
wherein σ is the median error, and n is the number of the point cloud data in the first point cloud set or the second point cloud set.
Preferably, the step of S4 is followed by the step of:
s5: and judging whether the current section is positioned on the left side or the right side of an intermediate wall of the large-diameter shield tunnel according to the intermediate error after the first point cloud set straight line is fitted and the intermediate error after the second point cloud set straight line is fitted.
Preferably, in the step S5:
when the median error after the first point cloud set straight line fitting is smaller than the median error after the second point cloud set straight line fitting, judging that the current section is positioned on the right side of the intermediate wall;
and when the median error after the first point cloud set straight line is fitted is larger than the median error after the second point cloud set straight line is fitted, judging that the current section is positioned on the left side of the intermediate wall.
Due to the adoption of the technical scheme, the invention has the following beneficial effects:
through the automatic acquisition of the point cloud of the large-diameter shield tunnel by the three-dimensional laser scanning device, the setting of the first included angle range and the second included angle range, the straight line fitting by combining the least square method and the calculation and judgment of the medium error, the technical effects that the partition wall of the large-diameter shield tunnel can be automatically identified according to the point cloud data and the manual operation time can be reduced are realized.
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Fig. 1 is a flowchart of a method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a section of a large-diameter shield tunnel according to an embodiment of the present invention;
fig. 3 is a cloud point diagram of fig. 2.
Detailed Description
The following description of the preferred embodiments of the present invention, in accordance with the accompanying drawings 1-3, will be provided to enable a better understanding of the functions and features of the invention.
Referring to fig. 1 to 3, a method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data according to an embodiment of the present invention includes:
s1: acquiring point cloud data of each section of each channel of a large-diameter shield tunnel 1 by using a three-dimensional laser scanning device, wherein the point cloud data comprises three-dimensional coordinates (X, Y and Z) of each scanning point in each section, wherein X represents a coordinate value of an X axis of the current section, Y represents a coordinate value of a Y axis of the current section, and Z represents a coordinate value of a Z axis of the current section; the X axis is arranged along the horizontal direction of the cross section, the Y axis is arranged along the axial direction of the current cross section, and the Z axis is arranged along the vertical direction of the current cross section.
In this embodiment, major diameter shield tunnel 1 adopts general two-sided wedge ring staggered joint to assemble, including controlling two passageways, every ring comprises 8 sections of jurisdiction, divide into 1 and seals a piece, 2 adjacent joint pieces, 5 standard blocks, and 1 radial position in major diameter shield tunnel sets up mid-board 11, separates the line of going up and down, generally only in the visual expert of other passageway department. Due to the perspective blocking effect of the intermediate wall 11, when the large-diameter shield tunnel 1 is scanned by adopting the three-dimensional laser, only scanning point cloud information in a single channel at the left side or the right side of the intermediate wall 11 can be acquired; in this embodiment, the center coordinates of the three-dimensional laser scanning device are set as the origin coordinates.
S2: and calculating an included angle theta formed by each scanning point and the vertical direction of the corresponding section.
S3: extracting different types of first point cloud sets and second point cloud sets from the point cloud data according to the included angle theta; the categories comprise tunnel segment end point cloud sets and mid-partition wall end point cloud sets.
Wherein the step of S3 further comprises the steps of:
s31: setting a first included angle range and a second included angle range;
s32: extracting point cloud data with an included angle theta in a first included angle range from the point cloud data to form a first point cloud set; and extracting point cloud data with the included angle theta in a second included angle range from the point cloud data to form a second point cloud set.
The first included angle range is: -127 ° < θ < -34 °; the second included angle range is as follows: 34 DEG < theta < 127 deg. The included angle theta is positive towards the positive direction of the X axis of the current section, and the included angle theta is negative towards the negative direction of the X axis of the current section.
S4: the categories of the first point cloud set and the second point cloud set are identified and determined.
Wherein S4 further comprises the steps of:
and performing linear fitting on the first point cloud set and the second point cloud set by adopting a least square method, wherein a linear equation is as follows: x-k-y + b, where k represents slope and b represents intercept;
respectively calculating the mean error after straight line fitting of the first point cloud set and the second point cloud set;
comparing the sizes of the two errors, wherein the first point cloud set or the second point cloud set corresponding to the smaller error is the middle partition wall endpoint cloud set; and the first point cloud set or the second point cloud set corresponding to the larger one-medium error is the tunnel segment end point cloud set.
In this embodiment, the step of calculating the medium error includes:
establishing an error equation vn：vn＝yn·k+b-xn(1)；
Wherein x isnIs the coordinate value of the current section X axis of the n point cloud data, ynThe coordinate value of the Z axis of the current section of the nth point cloud data is obtained;
according to error equation vnEstablishing an error matrix V;
wherein
Satisfy VTMin represents VTThe minimum value of V; solving to obtain:
the mean error is calculated using a mean error formula:
and the sigma is a medium error, and the n is the number of point cloud data in the first point cloud set or the second point cloud set.
S5: and judging whether the current section is positioned on the left side or the right side of an intermediate wall of the large-diameter shield tunnel according to the intermediate error after the first point cloud set straight line is fitted and the intermediate error after the second point cloud set straight line is fitted.
Wherein, in the step of S5:
when the median error after the straight line fitting of the first point cloud set is smaller than the median error after the straight line fitting of the second point cloud set, judging that the current section is positioned on the right side of the middle partition wall;
and when the median error after the straight line fitting of the first point cloud set is greater than the median error after the straight line fitting of the second point cloud set, judging that the current section is positioned on the left side of the intermediate wall.
For example, when the median error after the straight line fitting of the first point cloud set is smaller than the median error after the straight line fitting of the second point cloud set, the first point cloud is an end point cloud set of the intermediate wall, the current section corresponds to a right channel of the large-diameter shield tunnel 1, and the intermediate wall is located in the negative direction of the X axis; otherwise, the current section corresponds to the left channel of the large-diameter shield tunnel 1, and the intermediate wall is located in the positive direction of the X axis.
While the present invention has been described in detail and with reference to the embodiments thereof as illustrated in the accompanying drawings, it will be apparent to one skilled in the art that various changes and modifications can be made therein. Therefore, certain details of the embodiments are not to be interpreted as limiting, and the scope of the invention is to be determined by the appended claims.
Claims (7)
1. A method for automatically identifying a large-diameter shield tunnel mid-partition based on point cloud data comprises the following steps:
s1: acquiring point cloud data of each section of each channel of a large-diameter shield tunnel by using a three-dimensional laser scanning device, wherein the point cloud data comprises three-dimensional coordinates (X, Y, Z) of each scanning point in each section, wherein X represents a coordinate value of an X axis of the current section, v represents a coordinate value of a Y axis of the current section, and Z represents a coordinate value of a Z axis of the current section; the X axis is arranged along the horizontal direction of the section, the Y axis is arranged along the axial direction of the current section, and the Z axis is arranged along the vertical direction of the current section;
s2: calculating an included angle theta formed by each scanning point and the corresponding vertical direction of the section;
s3: extracting a first point cloud set and a second point cloud set of different types from the point cloud data according to the included angle theta; the categories comprise a tunnel duct piece end point cloud set and a mid-partition wall end point cloud set;
s4: identifying and determining a category of the first point cloud set and the second point cloud set;
the S4 further includes the steps of:
and performing straight line fitting on the first point cloud set and the second point cloud set by adopting a least square method, wherein a straight line equation is as follows: x-k-y + b, where k represents slope and b represents intercept;
respectively calculating the mean error after straight line fitting of the first point cloud set and the second point cloud set;
comparing the sizes of the two intermediate errors, wherein the first point cloud set or the second point cloud set corresponding to the smaller intermediate error is the intermediate wall endpoint cloud set; the first point cloud set or the second point cloud set corresponding to the larger medium error is the tunnel segment end point cloud set.
2. The method for automatically identifying a large-diameter shield tunnel mid-partition based on point cloud data as claimed in claim 1, wherein the included angle θ is positive towards the positive direction of the X axis of the current section, and the included angle θ is negative towards the negative direction of the X axis of the current section.
3. The method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data as claimed in claim 2, wherein the step of S3 further comprises the steps of:
s31: setting a first included angle range and a second included angle range;
s32: extracting the point cloud data of which the included angle theta is within the first included angle range from the point cloud data to form a first point cloud set; and extracting the point cloud data of which the included angle theta is within the second included angle range from the point cloud data to form the second point cloud set.
4. The method for automatically identifying a mid-wall of a large-diameter shield tunnel based on point cloud data according to claim 3, wherein the first included angle range is as follows: -127 ° < θ < -34 °; the second included angle range is as follows: 34 DEG < theta < 127 deg.
5. The method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data as claimed in claim 4, wherein the step of calculating the medium error comprises:
establishing an error equation vn：vn＝yn·k+b-xn(1)；
Wherein x isnIs the coordinate value of the current section X axis of the point cloud data of the nthnThe coordinate value of the current section Z axis of the nth point cloud data is obtained;
according to said error equation vnEstablishing an error matrix V;
V＝[v1，v2，...，vn]T，
L＝[x1，x2，…，xn]T
wherein
Satisfy VTMin represents VTThe minimum value of V; solving to obtain:
calculating the medium error by using a medium error formula:
wherein σ is the median error, and n is the number of the point cloud data in the first point cloud set or the second point cloud set.
6. The method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data according to claim 5, wherein the step of S4 is further followed by the steps of:
s5: and judging whether the current section is positioned on the left side or the right side of an intermediate wall of the large-diameter shield tunnel according to the intermediate error after the first point cloud set straight line is fitted and the intermediate error after the second point cloud set straight line is fitted.
7. The method for automatically identifying a mid-partition of a large-diameter shield tunnel based on point cloud data as claimed in claim 6, wherein in the step of S5:
when the median error after the first point cloud set straight line fitting is smaller than the median error after the second point cloud set straight line fitting, judging that the current section is positioned on the right side of the intermediate wall;
and when the median error after the first point cloud set straight line is fitted is larger than the median error after the second point cloud set straight line is fitted, judging that the current section is positioned on the left side of the intermediate wall.
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| CN110706153B (en) * | 2019-12-12 | 2020-04-10 | 湖南联智科技股份有限公司 | Tunnel section rapid extraction method based on original point cloud data |
| CN112907601B (en) * | 2021-03-30 | 2021-09-24 | 中铁工程装备集团隧道设备制造有限公司 | Automatic extraction method and device for tunnel arch point cloud based on feature transformation |
| CN113538385B (en) * | 2021-07-21 | 2022-10-25 | 上海勘察设计研究院(集团)有限公司 | Tunnel apparent disease type and grade discrimination method based on deep learning |
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Address after: 200093 No. 38 Shui Feng Road, Yangpu District, Shanghai. Patentee after: Shanghai Survey, Design and Research Institute (Group) Co.,Ltd. Address before: 200093 No. 38 Shui Feng Road, Yangpu District, Shanghai. Patentee before: SGIDI ENGINEERING CONSULTING (Group) Co.,Ltd. |